Kompy

Kompy is a unified ecommerce data API that provides structured Walmart marketplace data without the overhead of running and maintaining scrapers. It offers a single, clean interface for accessing products, search results, barcode lookups, seller offers, customer reviews, and comprehensive price and stock history. All data is returned as consistent, predictable JSON, making it immediately usable in any application or workflow. Kompy is built for both human developers and AI agents. You can call the REST API from any programming language, or point your AI agent at the included MCP server and it can query Walmart data directly. The platform is designed for quality over quantity, focusing on delivering reliable, high-fidelity data for the entire Walmart catalog. It is ideal for developers building price tracking tools, ecommerce analytics platforms, competitive intelligence systems, and AI-driven arbitrage bots. With Google sign-in, instant API key generation, and transparent credit-based pricing that scales from a side project to production, Kompy removes the friction typically associated with marketplace data acquisition. The service records the marketplace around the clock, capturing hourly snapshots of prices, stock levels, and buy-box changes for every tracked SKU, with full historical data available back to day one. This makes Kompy not just a data retrieval tool, but a comprehensive historical data platform for the Walmart ecosystem.

Unified REST API and MCP Server

Kompy provides a single, unified API that works over both plain HTTP and the Model Context Protocol (MCP). Every operation is a documented REST endpoint you can call from any language, and the same operations ship as a first-party MCP server so AI agents can access them as callable tools. This dual-access approach means you can build traditional applications using standard HTTP requests while simultaneously enabling AI agents to query Walmart data directly without additional integration work.

Full Historical Price and Stock Data

Kompy records the Walmart marketplace around the clock, capturing hourly snapshots of prices, stock levels, and buy-box changes for every SKU it tracks. The full price history, per seller, is available back to day one. Unlike other APIs that only offer current data, Kompy provides a complete historical record that enables trend analysis, price drop detection, and strategic purchasing decisions based on long-term market behavior.

Clean, Predictable JSON Responses

Every API response from Kompy returns a consistent JSON structure with a data object containing the requested information and a meta object with the request ID and latency. This deterministic schema eliminates the need for complex parsing logic and error handling. Responses are small, structured, and include timestamps, making them easy to process in any programming language or data pipeline without unexpected surprises.

Instant Onboarding and Credit-Based Pricing

Kompy offers Google sign-in for instant account creation and immediate API key generation. There are no lengthy approval processes or sales calls. The credit-based pricing model means you pay only for what you use, with transparent costs that scale from a side project to full production. Every account starts with free credits, allowing you to test the API thoroughly before committing to a paid plan.

Ecommerce Price Monitoring and Arbitrage

Developers and entrepreneurs can use Kompy to monitor Walmart prices in real time and identify profitable arbitrage opportunities on other marketplaces like Amazon. By using the search endpoint with price drop sorting and the history endpoint to analyze recent trends, users can automatically detect products with significant price gaps. For example, a user can scan Walmart clearance items and instantly identify products with a 30% or greater ROI margin when resold on Amazon, complete with exact price comparisons and profit calculations.

AI Agent-Powered Market Research

AI agents integrated with Kompy via the MCP server can autonomously conduct comprehensive market research on Walmart. An agent can search for products, retrieve full product records with prices and ratings, analyze price history trends, and fetch customer reviews all through simple tool calls. This enables conversational interfaces where users can ask questions like "find me the best value 4K TVs under $500 with good reviews" and receive structured, actionable results without writing any code.

Competitive Intelligence for Retailers

Retail businesses can leverage Kompy to gain deep insights into Walmart's pricing strategies and inventory patterns. By tracking specific product categories or competitor listings over time, companies can understand pricing dynamics, identify when Walmart adjusts prices, and see which sellers are winning the buy box. The historical data allows for retrospective analysis of pricing trends during major shopping events like Black Friday, providing valuable intelligence for strategic planning and pricing optimization.

Automated Inventory and Stock Alerting

Developers can build custom alerting systems that monitor stock levels for high-demand products on Walmart. Using Kompy's product endpoint, an application can check stock status for thousands of SKUs simultaneously and trigger notifications when items come back in stock or when prices drop below a predefined threshold. This is particularly useful for tracking limited-edition releases, clearance items, or products that frequently go out of stock, enabling users to act quickly on favorable market conditions.

What is the difference between using the REST API and the MCP server?

The REST API is designed for traditional application development where you make standard HTTP requests from any programming language to retrieve data. The MCP server provides the exact same data but exposes it as callable tools that AI agents can discover and use autonomously. Both use the same API key and credit system, so you can switch between them or use both simultaneously without any additional configuration or cost.

How does the credit-based pricing work?

Every API request consumes a certain number of credits based on the endpoint and complexity. Each plan includes a monthly credit allowance. When you make a request, credits are deducted from your account balance. You can monitor your usage in the dashboard and upgrade your plan when needed. Unused credits do not roll over to the next month. All plans include API access, MCP server access, and support, with higher tiers offering more credits and priority support.

What data is available in the price history?

Kompy records hourly snapshots of prices, stock levels, and buy-box changes for every SKU it tracks. The history is available per seller, meaning you can see not just the overall product price but which seller was offering it at what price at any given time. Historical data goes back to the day the product was first tracked by Kompy, providing a comprehensive view of market dynamics over time.

Can I use Kompy with AI tools like Claude Code or Cursor?

Yes, Kompy is designed to work seamlessly with AI agent frameworks that support MCP, including Claude Code, OpenClaw, Cursor, LangChain, OpenAI Agents SDK, and n8n. You simply add the MCP server configuration with your API key, and the agent can immediately start using all Kompy endpoints as callable tools. The same deterministic schemas and structured errors apply whether you are calling the API directly or through an agent.

Kompy offers three transparent pricing tiers designed to scale from individual developers to large teams. The Hobby plan at $49.99 per month includes 14,000 credits and is ideal for individuals getting started. The Pro plan at $149.99 per month includes 45,000 credits and is the most popular choice for professionals and small teams. The Business plan at $499.99 per month includes 180,000 credits and is designed for large teams with custom needs, including custom integrations. All plans include API access, MCP server access, and support, with priority support available on higher tiers. Every new account starts with free credits to test the service without any forced upgrade or hidden fees.